Chip designers usually rely on conservative supply voltage (Vdd) guardbands to prevent permanent faults as a consequence of CMOS process variations. Convolutional Neural Networks (CNNs) can be resilient to faults since they usually include significant amounts of data redundancy. This paper shows that the accuracy CNNs, is compromised when the Vdd of a CNN accelerator is reduced.
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